Name: Understanding COVID-19: The Role of Computational Intelligence
ISBN: 978-3-030-74761-9

Editors:

Janmenjoy Nayak⁰,
Bighnaraj Naik¹,
Ajith Abraham²

Janmenjoy Nayak
1. Department of Computer Science & Engineering, Aditya Institute of Technology and Management (AITAM) (An Autonomous Institution), Srikakulam, India
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Bighnaraj Naik
1. Department of Computer Application, Veer Surendra Sai University of Technology, Burla, India
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Ajith Abraham
1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, USA
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Presents advanced computational intelligence approaches spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, self-organizing systems, fuzzy systems, and hybrid intelligent systems in solving COVID-19
Covers novel computational intelligence and technological models for the purpose of effective COVID-19 solving at par with the standards laid down by the World Health Organization
Written by experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 963)

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Table of contents (23 chapters)

Front Matter

Pages i-xv

PDF
Learning from Various Modalities of COVID-19 Data
1. Front Matter
  
  Pages 1-1
  
  PDF
2. COVID-19 Pandemic: Theory, Concepts and Challenges
  
  Anindya Banerjee, Raj krishan Ghosh, Surajit Basak, Arijit Dey
  
  Pages 3-29
3. Evolutionary Algorithm Based Summarization for Analyzing COVID-19 Medical Reports
  
  Chirantana Mallick, Sunanda Das, Asit Kumar Das
  
  Pages 31-58
4. Chest CT in COVID-19 Pneumonia: Potentials and Limitations of Radiomics and Artificial Intelligence
  
  Federica Vernuccio, Giuseppe Cutaia, Roberto Cannella, Laura Vernuccio, Roberto Lagalla, Massimo Midiri
  
  Pages 59-76
5. Use of Deep Learning Based Frameworks on Pixel Scaled Images of Chest CT Scans for Detection of COVID-19
  
  Sushant Shetty, Amit Gawade, Subodh Deolekar
  
  Pages 77-99
6. SARS-CoV-2 Infection and Antibody-Dependent Enhancement
  
  Aliye Bastug, Hurrem Bodur
  
  Pages 101-113
7. Graph-Based Clustering Algorithm for Social Community Transmission Control of COVID-19 During Lockdown
  
  Varun Nagesh Jolly Behera, Ashish Ranjan, Motahar Reza
  
  Pages 115-139
8. COVID-19 Recommendation System of Chest X-Ray Images Using CNN Deep Learning Technique with Optimizers and Activation Functions
  
  Niyati Sinha, Puhup Karjee, Riddhi Agrawal, Ankita Banerjee, Chittaranjan Pradhan
  
  Pages 141-163
9. Application of Deep Learning Techniques for COVID-19 Management
  
  Rajan Gupta, Anshuman Gupta, Manan Bedi, Saibal K. Pal
  
  Pages 165-197
Prediction and Risk Analysis of COVID-19 Susceptibility
1. Front Matter
  
  Pages 199-199
  
  PDF
2. An Exploratory Study of Disaster Risk Management Mobile Applications in Pandemic Periods
  
  K Saravanan, K. Ramesh, V. Sri Vigna Hema, S. Viganesh
  
  Pages 201-223
3. Potential of Deep Learning Algorithms in Mitigating the Spread of COVID-19
  
  Oluwafemi A. Sarumi, Ons Aouedi, Lawan J. Muhammad
  
  Pages 225-244
4. Predicting Antiviral Drugs for COVID-19 Treatment Using Artificial Intelligence Based Approach
  
  Ayan Banerjee, Soumen Kumar Pati
  
  Pages 245-269
5. Geographic Spread and Control of 2019-nCoV in the Absence of Vaccine
  
  Himadri Shekhar Mondal, Motahar Reza, Prasanta Sahoo
  
  Pages 271-290
6. Machine Learning Based Anxiety Prediction of General Public from Tweets During COVID-19
  
  Shubham Tribedi, Anuraag Biswas, Swarup Kr Ghosh, Anupam Ghosh
  
  Pages 291-312
7. A Role of Emerging Technologies in the Design of Novel Framework for COVID-19 Data Analysis and Decision Support System
  
  S. Rama Krishna, Mohammad Sirajuddin
  
  Pages 313-337
8. Gaussian Regression Models for Day-Level Forecasting of COVID-19 in European Countries
  
  Umut Özkaya, Şaban Öztürk
  
  Pages 339-356
9. Computational Intelligence Based Hybrid Hyperparameter Tuned Prediction Techniques for COVID-19 Epidemiological Data
  
  S. Dhamodharavadhani, R. Rathipriya
  
  Pages 357-375
Combating COVID-19 with Advanced Computational Intelligence Techniques
1. Front Matter
  
  Pages 377-377
  
  PDF

About this book

This book provides a comprehensive description of the novel coronavirus infection, spread analysis, and related challenges for the effective combat and treatment. With a detailed discussion on the nature of transmission of COVID-19, few other important aspects such as disease symptoms, clinical application of radiomics, image analysis, antibody treatments, risk analysis, drug discovery, emotion and sentiment analysis, virus infection, and fatality prediction are highlighted. The main focus is laid on different issues and futuristic challenges of computational intelligence techniques in solving and identifying the solutions for COVID-19. The book drops radiance on the reasons for the growing profusion and complexity of data in this sector. Further, the book helps to focus on further research challenges and directions of COVID-19 for the practitioners as well as researchers.

Keywords

Editors and Affiliations

Department of Computer Science & Engineering, Aditya Institute of Technology and Management (AITAM) (An Autonomous Institution), Srikakulam, India

Janmenjoy Nayak
Department of Computer Application, Veer Surendra Sai University of Technology, Burla, India

Bighnaraj Naik
Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, USA

Ajith Abraham

Bibliographic Information

Book Title: Understanding COVID-19: The Role of Computational Intelligence
Editors: Janmenjoy Nayak, Bighnaraj Naik, Ajith Abraham
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-74761-9
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-74760-2Published: 28 July 2021
Softcover ISBN: 978-3-030-74763-3Published: 29 July 2022
eBook ISBN: 978-3-030-74761-9Published: 27 July 2021
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XV, 569
Number of Illustrations: 61 b/w illustrations, 173 illustrations in colour
Topics: Computational Intelligence, Data Engineering, Artificial Intelligence

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Table of contents (23 chapters)

Front Matter

Learning from Various Modalities of COVID-19 Data

Front Matter

Prediction and Risk Analysis of COVID-19 Susceptibility

Front Matter

Combating COVID-19 with Advanced Computational Intelligence Techniques

Front Matter

About this book

Keywords

Editors and Affiliations

Department of Computer Science & Engineering, Aditya Institute of Technology and Management (AITAM) (An Autonomous Institution), Srikakulam, India

Department of Computer Application, Veer Surendra Sai University of Technology, Burla, India

Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, USA

Bibliographic Information

Publish with us

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